BEGIN:VCALENDAR PRODID;X-RICAL-TZSOURCE=TZINFO:-//Calagator//EN CALSCALE:GREGORIAN X-WR-CALNAME:Calagator METHOD:PUBLISH VERSION:2.0 BEGIN:VTIMEZONE TZID;X-RICAL-TZSOURCE=TZINFO:America/Los_Angeles BEGIN:DAYLIGHT DTSTART:20240310T020000 RDATE:20240310T020000 TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT CREATED;VALUE=DATE-TIME:20240821T004642Z DTEND;TZID=America/Los_Angeles;VALUE=DATE-TIME:20240919T130000 DTSTART;TZID=America/Los_Angeles;VALUE=DATE-TIME:20240919T120000 DTSTAMP;VALUE=DATE-TIME:20240821T004642Z LAST-MODIFIED;VALUE=DATE-TIME:20240821T004642Z UID:http://calagator.org/events/1250481269 DESCRIPTION:Semantic Layer Architecture: Top Applications and Implementat ion Approaches for Enterprise Data Management (with Real World Examples) \;\n \;\nOver the last decade\, we have seen some of the most ex citing innovations emerge within the enterprise knowledge and data manag ement spaces. Those innovations with real staying power have proven to d rive business outcomes and prioritize intuitive user engagement. Within this list are a semantic layer (for breaking the silos between knowledge and data) and of course\, generative AI (a topic that is often top of m ind on today’s strategic roadmaps). Both have one thing in common—they a re showing promise in addressing the age-old challenge of unlocking busi ness insights from organizational knowledge and data\, without the compl exities of expensive data\, system\, and content migrations. \;\n 3\;\nIn 2019\, Gartner published research emphasizing the end to “a sing le version of the truth” for data and knowledge management and that by 2 026\, “active metadata” will power over 50% of BI and analytics tools an d solutions to provide a structured and consistent approach to connectin g instead of consolidating data. \;\n \;\nBy employing semantic components and standards (through metadata\, business glossaries\, taxon omy/ontology\, and graph solutions)\, a semantic layer arms organization s with a framework to aggregate and connect siloed data/content\, explic itly provide business context for data\, and serve as the layer for expl ainable AI. \;\n \;\nThis session will present case studies that take a deep dive in the technical architecture of a Semantic Layer\, exp loring the components that enable semantic capabilities\, such as metada ta management\, data catalogs\, ontology/knowledge graphs and AI infrast ructure. The presentation will emphasize how these components interconne ct organizational knowledge and data assets\, enhancing systems like rec ommendation engines and semantic search and explore the top three common approaches we are seeing at play in order to weave this data and knowle dge layer into the fabric of enterprise architecture\, highlighting the applications and organizational considerations for each. \;\n \;\n \;\nSPEAKERS \;\n \;\nLulit Tesfaye is a Partner and the Vice President for Knowledge &\; Data Services and Engineering at Enterpri se Knowledge\, LLC.\, the largest global consultancy dedicated to Knowle dge and data management. Lulit brings over 15 years of experience leadin g global information and data management initiatives\, specializing in t echnologies and integrations. Lulit is most recently focused on employin g advanced Enterprise AI\, knowledge graphs\, and semantic layer capabil ities for optimizing enterprise data and information assets. \;\n \;\nUrmi Majumder is a Principal Architect at Enterprise Knowledge\, whe re she leads system architecture\, design\, and implementation of a broa d range of enterprise solutions. She has 15 years of experience leading the development of technical solutions in support of a wide variety of f ederal and commercial clients by integrating open-source\, SaaS\, and CO TS tools and establishing the connection between these tools and their b usiness users. Her diverse portfolio includes the design and developmen t of data-centric solutions\, including content management systems\, rec ord management systems\, knowledge portals\, search applications\, seman tic applications\, data catalogs\, and AI/ML applications\, both in the context of new system development and data modernization efforts. \;\ n\n\nTags: data\, datagovernance\, datamodels\, datamodeling\, cloud\, D AMA\, datapdx\, governance\, semanticlayer\n\nImported from: http://cala gator.org/events/1250481269 URL:https://datapdx.org/2024/08/20/september-2024-semantic-layer-architec ture/ SUMMARY:Data PDX: Semantic Layer Architecture: Top Applications and Imple mentation Approaches LOCATION:Google Meet: false SEQUENCE:1 END:VEVENT END:VCALENDAR